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Industry
e-commerce
Skills
data-wrangling
Tools
sql
python
Learning Objectives
Demonstrate data wrangling concepts with SQL.
Apply aggregate functions in SQL to summarize and analyze data.
Use different SQL joins to combine data from multiple tables effectively.
Perform data cleaning tasks in Python using Pandas, including handling missing values and filtering data.
Implement aggregations in Pandas using functions like groupby(), sum(), mean(), and count().
Write and use Python functions to organize and reuse code efficiently.
Design queries to extract, filter, and combine data for analysis.
Overview
GlobalMart, a fast-growing e-commerce company, offers a wide range of products across Technology, Office Supplies, and Furniture in the North American market. Efficient inventory management is crucial for the business, as both overstocking and stockouts can impact profitability.
In this scenario, we will analyze product sales, delivery records, and vendor performance to help Category Managers track fast-moving and slow-moving products. By exploring transaction data and product attributes, we’ll uncover insights such as top-performing subcategories, sales quantities, purchase frequency, and the influence of product images on sales. These findings will guide better inventory, marketing, and supply chain decisions at GlobalMart.
Prerequisites
- Knowledge of basic SQL concepts like SELECT, WHERE, GROUP BY, HAVING, ORDER BY, and JOIN.
- Ability to work with aggregate functions such as COUNT(), SUM(), AVG(), and FORMAT().
- Knowledge of different join types, such as INNER JOIN, LEFT JOIN, and when to use them.
- Knowledge of basic Python concepts like variables, data types (int, float, string), lists, tuples, dictionaries, and their usage.
- Ability to use Pandas for data cleaning tasks such as handling missing values, filtering rows, and selecting specific columns.
- Ability to perform aggregations in Pandas using functions like groupby(), sum(), mean(), and count().
- Familiarity with defining and using functions in Python